snapshot...

modules/deeplearning/cnn_cld_frac_mod_res.py

@@ -186,7 +186,7 @@ def get_min_max_std(grd_k):
     std = np.nanstd([a, b, c, d], axis=0)
     avg = np.nanmean([a, b, c, d], axis=0)
 
-    return lo, hi, std, mean
+    return lo, hi, std, avg
 
 
 def get_label_data(grd_k):
@@ -353,10 +353,11 @@ class SRCNN:
             idx = params.index(param)
             tmp = input_data[:, idx, :, :]
 
-            lo, hi, std = get_min_max_std(tmp)
+            lo, hi, std, avg = get_min_max_std(tmp)
             lo = normalize(lo, param, mean_std_dct)
             hi = normalize(hi, param, mean_std_dct)
             std = np.where(np.isnan(std), 0, std)
+
             data_norm.append(lo[:, 0:66, 0:66])
             data_norm.append(hi[:, 0:66, 0:66])
             data_norm.append(std[:, 0:66, 0:66])